 Combining multiple spatial analysis methods offers more powerful intelligence for both immediate interventions and long-term strategy. Research from the Rutgers Center on Public Security finds that combining multiple spatial analysis methods offers more powerful intelligence for both immediate interventions and long-term strategy. Hotspot mapping, near repeat analysis, and environmental risk modeling each provide distinct insights:
There's three key findings from the research. First, crime clusters are not just functions of past incidents; they are deeply tied to environmental features like bus stops, schools, and nightlife venues. Second, near repeat events — where new crimes occur close in space and time to prior incidents — are influenced by both past crime and place-based risks. And finally, integrating analytic methods provides a composite risk picture that is more actionable (and predictive) than any single technique. Therefore, a 3-stage, integrated process for analyzing crime incident location data can produce layered insights for tactical response (prioritize deployments to emergent hot spots), temporal strategy (anticipate windows of elevated risk for repeat incidents), and strategic prevention (focus interventions on high-risk environments before crimes concentrate). Clear Takeaways
Repeating analytic processes that bring together diverse tools and techniques — from hotspot and near repeat analysis to risk terrain modeling — is the best approach to informing operations and driving meaningful action in public safety. Technology platforms like ActionHub by Simsi further support this by enabling analysts and practitioners to operationalize complex spatial insights into clear, actionable strategies that involve multiple agencies and partners who can focus their resources and expertise at key settings. Hot spots are one of the most influential and productive ideas in 21st century crime analysis. For police leaders, analysts, and public safety professionals, hot spot maps offer an immediate and compelling picture of where crime concentrates. They are practical, intuitive, and operationally useful. More importantly, hot spot analysis reflects one of the most consistently validated findings in criminology: crime is not randomly distributed across geography—it clusters in places. The value of hot spot mapping is not just that it helps agencies visualize crime. It helps people think spatially. It forces decision-makers to recognize that crime prevention is not only about offenders or victims—it is also about places, and the unique features of places that produce recurring crime patterns. In that sense, hot spot mapping has done more than improve crime analysis. It has elevated spatial awareness in policing. It has helped agencies shift away from generalized assumptions and toward focused place-based strategies. Hot spot policing has become a foundation for evidence-based practice precisely because it takes a complex problem and makes it immediately actionable. Crime hot spots are the "squeaky wheel" of crime problems. That is, they get the attention of local resources because it's an easy signal to tune-in to. But hot spots also invite an important follow-up question—one that many analysts and commanders ask instinctively as soon as they see the map: Why is this hot spot a hot spot? This is where the idea of spatial intelligence becomes essential, and where Risk Terrain Modeling (RTM) adds a powerful, complementary layer to hot spot analysis. Hot Spots Are More Than Clusters—They Are Spatial Signals Hot spots are often treated as the end product of crime analysis: the map shows the cluster, the cluster becomes the deployment target, and resources flow accordingly. But in practice, hot spots should be understood as spatial signals—visible indicators of deeper conditions shaping crime patterns. In other words, hot spots are not just places where crime is occurring. They are places where the environment is likely producing opportunities for crime. Hot spots persist not because offenders randomly return there, but because certain locations contain features, or elements, that make crime easier to commit, harder to detect, or more rewarding to repeat. These elements can include routine activity patterns, physical design characteristics, business activity, transportation access, guardianship levels, and other situational factors. When viewed through this lens, hot spot maps become more than tactical tools—they become starting points for deeper inquiry. Spatial Intelligence and the “Risky” Nature of Places Crime analysts have long recognized that the same types of locations appear again and again in hot spot maps. Certain environments—certain facilities, certain land uses, certain structural conditions—show up repeatedly in places where violence, property crime, or disorder concentrates. These are not random coincidences. They reflect a basic reality: some places are inherently riskier than others, not because they are “bad neighborhoods,” but because the environment creates situational opportunities for crime. This is where the logic of hot spot mapping naturally extends into the logic of Risk Terrain Modeling.
RTM treats geographic space as an intelligence system. It does not diminish the value of hot spot mapping; instead, it embraces it as a sign or symptom of the settings in need of attention and a spatial diagnosis. RTM is merely another tool in the toolkit to strengthen an analyst’s ability to interpret hot spots by identifying the environmental features that help generate them. (Below) Video shows FREE mapping tools in the ActionHub software From Hot Spot Mapping to Risk Terrain Modeling
Hot spot analysis is rooted in the distribution of crime incidents. RTM harnesses that foundation and shifts the analytic focus toward the environmental features that influence why crime is most likely to occur. RTM identifies and tests risk factors such as: liquor stores, bars and nightlife locations, abandoned or vacant properties, bus stops and transit hubsconvenience stores, motels, poorly maintained lots or alleys. These risk factors are mapped and analyzed in combination. RTM does not assume that a single feature explains crime patterns. Instead, it evaluates how multiple factors overlap and interact across geography to produce elevated risk. The result is a risk terrain map that highlights places where the environment is most conducive to crime—places that may align with existing hot spots, and sometimes places that have not yet become hot spots but may soon. This is a crucial point for practitioners: RTM can help identify emerging hot spots by identifying the risk context before crime patterns fully materialize. Hot Spots and Risk Terrains Work Best Together Hot spot mapping plus RTM equals strategic analysis. Hot spot mapping is excellent for:
RTM is excellent for:
In practice, these approaches strengthen one another. Hot spot maps show where crime is concentrated. Risk terrain maps explain the environmental backstory behind that concentration. Together, they transform “hot spot policing” into something more sustainable: hot spot prevention. Crime prevention is rarely achieved through enforcement alone. Many of the strongest interventions are rooted in place management: improving lighting, remediating abandoned properties, strengthening guardianship, regulating problematic facilities, and coordinating services. Hot spot mapping identifies where the problem is happening. RTM helps clarify what needs to change in the environment for the problem to stop happening. Turning Hot Spot Awareness into Spatial Intelligence Hot spot mapping has given policing and crime analysis a practical way to see that crime is concentrated and that place matters. Risk terrain modeling builds on that by diagnosing where else crime is most likely to happen and why. This is not a theoretical distinction. It is the difference between responding to crime concentrations and strategically reducing the environmental conditions that sustain them. In that way, RTM is best understood as deep dive into the hot spot philosophy—one that reveals crime patterns and the spatial intelligence behind the patterns. And when hot spot mapping and RTM are used together, cities are better equipped not only to respond to crime—but to prevent it. Modern policing is expected to be proactive rather than reactive. But being proactive requires more than good instincts or experience—it requires a structured way of identifying risk, interpreting intelligence, and coordinating effective responses.
That is why intelligence-led policing must be paired with a clear framework for decision-making. That is, a practical method for translating uncertainty, threat information, and analytical findings into operational strategies that can be implemented, evaluated, and improved over time. To address this need, Kennedy and Van Brunschot (2009) proposed a structured framework for incorporating risk into police decision-making in their book The Risk in Crime. It's the ACTION Risk Analysis Model. The name is intentional. Unlike acronyms that feel forced or detached from their purpose, ACTION reinforces what modern policing demands--a mindset of initiative, prevention, and measurable results. Why Risk Frameworks Matter in Modern Policing Police agencies face complex and evolving crime problems, often involving:
Risk-based decision-making helps agencies prioritize where attention is needed most. It strengthens accountability by clarifying why certain decisions are made, and it improves governance by ensuring that intelligence-led strategies are supported by consistent processes rather than informal judgment. The ACTION model provides a way to do this systematically. The Six Elements of the ACTION Risk Analysis Model The ACTION model is built around six core steps. Together, they guide agencies from assessment to analysis, from planning to organizational improvement, and from internal awareness to broader communication. A — Assess Vulnerabilities, Exposure, and Threats Effective policing begins with assessment. Before strategies are developed or resources are deployed, agencies must understand the nature of the risk environment. This stage focuses on four related components: 1. Uncertainty Uncertainty refers to what is not yet known—but must be clarified. Key questions include:
Outcome: A narrative that identifies what is known, what is unknown, and what can reasonably be predicted based on intelligence and past findings. 2. Exposure Exposure describes how crime affects communities and police resources. Key questions include:
Outcome: An analysis of active groups, past events, and an inventory of existing policies or interventions aimed at reducing exposure. 3. Vulnerability Vulnerability refers to weak points—targets, locations, systems, or behaviors—that increase the likelihood of harm. Key questions include:
Outcome: A tactical assessment of protective strategies and the resources needed to mitigate harm. 4. Threat Threat assessment focuses on identifying specific actors or behaviors that represent immediate or emerging danger. Key questions include:
Outcome: Threat bulletins and recommendations for resource deployment and tactical decisions. C — Create Connections Through Analysis Assessment is not enough. Intelligence-led policing requires agencies to interpret information and make connections between patterns, causes, and consequences. This step involves:
Outcome: Actionable intelligence products such as:
This step is often where agencies begin shifting from “what happened” to “why it happened”—a critical move for long-term prevention. Understanding "why there?" is core to Risk Terrain Modeling (RTM) analysis. T — Task Strategies to Respond and Prevent Once risks are assessed and analyzed, agencies must define practical tasks that reduce harm. This stage focuses on three major categories:
This is where intelligence becomes operational. ActionHub is a primary software tool this type of strategic, coordinated response. Outcome: Programs and strategies that directly address identified vulnerabilities and threats, including:
I — Integrate Intelligence and Information Risk analysis is only as strong as the quality of information supporting it. Agencies must define what “intelligence” means operationally and ensure it is usable. Key questions include:
Outcome: Improved feedback loops, including:
This ensures intelligence is not simply collected—but actually used. O — Optimize and Refine the Organization Intelligence-led policing requires organizational structure that supports it. Agencies must ensure that reporting relationships, accountability mechanisms, and monitoring capacity align with risk-based decision-making. This includes:
Outcome: Organizational improvements such as:
N — Notify Others and Build Risk Awareness Risk reduction is not achieved in isolation. Communication—internally and externally—is a critical part of effective intelligence-led policing. This step includes:
Outcome: Tools and initiatives such as:
The open Learning Management System (LMS) built directly into ActionHub makes structured communication a form of professional development or continuing education training that can be asynchronous and managed across the agency for compliance. A Framework Designed for Real-World Policing The ACTION model is more than a conceptual tool. It is designed to support:
Most importantly, it helps agencies translate complex crime problems into structured responses. It provides a consistent process for asking the right questions, producing the right intelligence products, and implementing strategies that are measurable and defensible. Final Takeaway: Intelligence Becomes Useful When It Leads to ACTION Intelligence-led policing is not simply about collecting information. It is about using information to understand risk, reduce vulnerability, prevent harm, and coordinate meaningful intervention. The ACTION Risk Analysis Model offers a practical organizing device to guide police agencies through that process—from uncertainty and threat assessment to prevention, planning, and communication. In today’s policing environment, agencies need more than intelligence. They need a framework that turns intelligence into outcomes. They need ACTION. A recent study in the American Journal of Criminal Justice (open access) provides new evidence on how the public perceives “hot spots” policing — a highly used crime reduction strategy that focuses law enforcement resources on small geographic areas with persistent crime problems.
Although decades of research show that hot spots policing can reduce crime, public attitudes toward these strategies have been less well understood — especially how different types of information influence those attitudes. This study used a large preregistered survey experiment (N = 2,412) whereby respondents were randomly assigned to receive:
Findings suggest that public support for hot spots policing improves when crime reductions are clearly communicated alongside acknowledgement of community concerns. Why These Findings Matter for Policy and Practice: Hot spots policing is widespread — with estimates suggesting many departments now rely on this approach for resource allocation and public safety outcomes. This study highlights three practical insights that could help modify existing practices to better align them with operational needs and community expectations:
How It Connects to Broader Crime Prevention Strategy: A plethora of evidence makes it increasingly clear that hot spots policing is most effective when paired with community engagement and multi-stakeholder collaboration. Traditional enforcement-centric approaches can miss the nuanced ways communities interpret police activity; supplementing them with community-focused programming and broader place-based crime prevention resources helps:
To replicate and sustain evidence-based public safety strategies — where policing effectiveness and meaningful positive community engagement reinforce each other — policymakers and practitioners need supportive infrastructure. ActionHub, for example, is a powerful platform built by Simsi in partnership with Rutgers University and designed to:
Technology-enhanced practice makes community-focused and multi-stakeholder public safety not only more accessible, but more sustainable. Let’s invest in approaches that work — and in the tools that make them easier and more collaborative for everyone. A recent study highlighted by Boston University offers strong evidence that violence can be prevented when public safety systems invest in coordinated, community-centered responses rather than relying on enforcement alone. The research examined outcomes from the Violence Intervention Advocacy Program (VIAP) at Boston Medical Center and found that patients who consistently engaged with hospital-based violence intervention services after being treated for gunshot or stab wounds were about 50 percent less likely to be reinjured or later commit violence within two to three years. For policymakers and practitioners, this finding reinforces a critical takeaway: violence prevention works best when it is treated as a cross-sector responsibility—one that blends public health, social services, community organizations, and public safety agencies into a shared strategy. This also means that violence prevention is not a one-time intervention. It requires sustained coordination, follow-through, and accountability across systems. The VIAP study findings align with broader evidence supporting community-focused, multi-stakeholder public safety models. When local governments invest in partnerships among hospitals, community-based organizations, behavioral health providers, businesses, and law enforcement, they reduce duplication, close service gaps, and deliver more durable outcomes. This approach shifts public safety from a reactive posture to a preventive one—focused on reducing risk before harms are repeated. For leaders responsible for policy, funding, and implementation, the implication is clear: successful violence prevention requires both programmatic capacity and operational infrastructure. As these initiatives scale, tracking engagement activities and coordinating across agencies becomes increasingly complex without the right systems in place. This is where supportive technology becomes essential. Platforms like Simsi’s ActionHub are designed to help communities implement and manage collaborative public safety strategies. Agencies and community partners need tools to coordinate interventions, document actions, share insights, and align around shared goals—all while maintaining transparency and accountability. The Boston University study makes one thing unmistakably clear: violence is preventable when communities organize around evidence, collaboration, and sustained engagement. The challenge is replication and sustainability, and that's where combining the right partnerships with supporting technology is paramount to sustained success. The evidence is strong that violence prevention and harm reduction are well within reach when systems work together. In cities across the United States, a fundamental shift is occurring in how we approach community safety. For decades, the weight of public safety has rested almost exclusively on the shoulders of law enforcement. But as many police chiefs or mayors have said: Public safety is a team sport. And, “we can’t arrest our way out” of crime problems.
When we treat crime prevention as a "police-only" issue, we miss the opportunity to address the root causes found in our environment—the lighting, the vacant lots, and the specific businesses or land uses that can either invite or deter opportunities for crime and victimization. More importantly, we miss the chance to share the workload across the entire city ecosystem. We’ve seen what happens when cities stop working in silos and start working in sync. The results—ranging from a 63% drop in robberies in Atlantic City to a 22% reduction in gun violence in Kansas City—prove that when we coordinate our resources, we don't just "manage" crime; we prevent it. The Problem: The "Invisible" Work of Safety Law enforcement professionals are increasingly asked to coordinate work across multiple government agencies and community partners. Yet, they are often expected to do so without a shared system to manage projects or align priorities. This leads to a "visibility gap." There is a massive amount of "invisible" work happening every day—the partnership meetings, the community engagements, and the environmental fixes. Because this work doesn’t show up on a 911 call or a standard police report, it often goes uncounted and uncredited. In local government, visibility is currency. If you can’t document the effort, it is difficult to advocate for the resources your team deserves or to tell the full story of your success to the public. The Solution: An Operating System for Teamwork That is why we partnered with Simsi to build ActionHub. ActionHub is the operating system for teamwork and community engagement. It is a place-based project management and cross-agency collaboration platform purpose-built for the high stakes of public safety. It allows city leaders to visualize their entire safety ecosystem in one shared workspace. With ActionHub, you can finally:
By professionalizing community engagement and making the "invisible" work visible, ActionHub turns your safety strategy into a permanent city asset. It provides PIOs and media relations units with a real-time engagement dashboard, giving them the data they need to demonstrate the impact your team is making every single day. The best part? ActionHub is ready when you are! Experience the power of cross-agency collaboration for FREE. No gatekeepers, no sales pressure—just a powerful tool at your fingertips, made possible through Simsi's partnership with Rutgers University. Visit actionhub.simsi.com and click "Sign-Up Now."
Local police departments now have the capacity to do what's routinely done in the corporate sector, whereby private businesses seek to ensure that the risk management mission is instituted enterprise-wide and provides communication channels to various decision-makers and partners for asset protection and security threats. For public safety professionals, in addition to responding to crime incidents as they happen, ActionHub enables police management practices that optimize prevention, response, and mitigation to crimes and crime risks -- both at current hot spots and other vulnerable areas.
Guided by Simsi Analytics, the ActionHub compiles data-informed judgments to reduce uncertainty in the mission of crime risk governance for the goal of sustainable public safety. It extends the strong tradition of geographic analysis in the policing profession and takes advantage of contemporary analytical and technical tools like Risk Terrain Modeling (RTM) to improve and extend this history. What ActionHub demonstrates is that police leaders can tell patrol officers where to go to confront crime but also, based on their understanding of spatial vulnerabilities and recent past exposures, what to do when they get there, and how they can get other stakeholders engaged in the process. Police leaders are increasingly realizing that the burden of public safety needs to be shared in order to manage crime threats before problems emerge or cluster. ActionHub is the platform that empowers police to prevent crime and assign shared responsibility for public safety. Check out this eBook to see how ActionHub fits with DICE™ and Risk-Based Policing. For nearly two decades RTM has aided in the task of determining threats in an environment and marshaling resources to moderate the worst effects. But to efficiently and effectively act on risk assessments, police agencies must also enlist the support of a variety of other stakeholders. ActionHub enables this and empowers police to coordinate local resources and partners in convincing ways. The result is sustainable crime risk governance, measurable crime reductions, and enhanced public safety everywhere.
Modern policing has reconsidered the concept of place, shifting the focus to micro-units of analysis—such as block faces or street segments—that better reflect the scale at which public safety issues arise. This shift has brought renewed interest in environmental criminology theories, including routine activities, rational choice, crime pattern theory, and the theory of risky places. These perspectives help explain why crime concentrates in certain locations and how environmental factors influence criminal behavior.
The central role of place in policing is reinforced by the proven successes of place-based prevention strategies. Geographically focused strategies have had some of the strongest records of effectiveness, a conclusion supported by systematic reviews and meta-analyses. By integrating risk terrain modeling and other analytics that go "beyond hot spots", policing agencies can better understand the structural factors that contribute to crime at specific locations. This allows for more effective crime prevention strategies that go beyond traditional enforcement measures, aligning policing efforts with broader public safety goals.
In Cohen and Felson's original article on routine activities back in 1979, they wrote "the risk of criminal victimization varies dramatically among the circumstances and locations in which people place themselves and their property". It follows that motivated offenders commit crimes against suitable targets at certain places according to the environmental characteristics of those places, making it easier to complete crimes successfully and evade capture. Therefore, the context of high-crime places should be incorporated into crime prevention programming. Until the advent of Risk Terrain Modeling (RTM), this had yet to occur on a widespread basis, partly due to the then current analytical products commonly used in place-based interventions. Hot spot maps, for instance, show the concentration of crime but offer little insight into the physical structure of these places. This is akin to what Reboussian et al. (1995) refer to as a "mapless map"—a mere description of crime distribution without an analysis of why crime clusters in specific locations. Mapless maps have facilitated hot spot policing activities that are largely one-dimensional, focusing primarily on concentrating resources in high-crime places. However, little problem-oriented policing (POP) or S.A.R.A. effort has been given to modifying the features of places that attract illegal behaviors or give rise to crime. As Anthony Braga explained in 2015, "Too many police departments seem to rely on over-simplistic tactics, such as ‘putting cops on dots’ or launching indiscriminate zero-tolerance initiatives rather than engaging a coherent crime prevention strategy." Malcolm Sparrow reinforced this critique in 2016: "For anyone familiar with crime analysis, this is not new. And it is particularly not new when the default intervention strategy involves putting cops on dots." Jeffrey Brantingham, founder of a former predictive policing software company, explained that in response to place-based predictions, officers are instructed to use their "knowledge, skills, experience, and training in the most appropriate way to stop crime" (Huet, 2015). Ambiguity about what to do at crime hot spots is not surprising, and follows a recurring theme in policing whereby technological advancements often reinforce established analytic and tactical approaches rather than foster new and innovative ones. Over a six-year study, Peter Manning found that crime mapping and information technology were never used to challenge existing strategies but rather adapted to support current practices. How can the scope of place-based policing practices be expanded to incorporate the structure of criminogenic places? The answer may lie in moving beyond hot spots. Sparrow contends that "the only way to break out of this circularity trap—where operational methods determine what analyses are commissioned, and the analyses conducted determine the types of problems that are detected—is to throw wide open the analytic operation and demand much greater versatility… By deliberately increasing the versatility of the analytic operation, the organization increases the range of problems it can detect. Discovering new types of problems, in turn, then challenges the organization to develop relevant and novel operational responses." To be clear, current analytical products serve police well in many respects, given the demonstrated crime prevention utility of place-based approaches. But an honest reflection of the status quo highlights the importance of evaluating police responses not just by crime reduction but also in terms of efficiency, risk governance, and cost-effectiveness. Simsi Analytics, with risk terrain modeling, provides a more in-depth understanding of how structural factors and the interactions of people at places facilitate crime emergence and persistence. Simsi helps agencies expand the scope of place-based policing, enabling chiefs and mayors to enhance risk governance. This is how many cities are serving their communities with data-informed, justifiable actions for crime prevention and service delivery. Paraphrased from "Risk-Based Policing" by Kennedy, Caplan & Piza (2018). See this book for complete references cited here.
Crime analysis has been invaluable to the development of contemporary police strategies. However, a review of the literature suggests that there is room for improvement in how police analyze crime problems.
CompStat, when initially developed by the NYPD in the early 1990s, adhered to four main principles: 1) accurate and timely intelligence; 2) rapid deployment; 3) effective tactics; and 4) relentless follow-up and assessment. While NYPD’s original intent with CompStat was to enhance problem-solving capacities, later efforts in New York City and elsewhere disproportionately emphasized the "relentless follow-up and assessment" principle. This shift in focus transformed CompStat into a process where "analysis" rarely strayed beyond tallying crime counts and comparing numbers from current and prior periods. This limited approach diminished the role of problem-solving in favor of reinforcing standard police responses and bureaucratic models of organization. As Malcolm Sparrow articulated in 2016, police departments around the U.S. largely implemented CompStat programs as "de facto substitutes for any broader problem-solving approach, thereby restricting or narrowing both the types of problems police can address and the range of solutions they are able to consider." The end result is police commanders making assumptions, failing to control for uncertainties, and taking disproportionate operational responses based on minor, often insignificant, differences in crime counts. Research has consistently shown that crimes cluster at specific locations, with such clustering persisting over extensive time periods in certain cases. Given that crime patterns are spatially concentrated, many scholars including Anthony Braga, Andrew Papachristos and David Hureau have argued that crime prevention resources "should be similarly concentrated rather than diffused across urban areas" to achieve maximum impact. Risk terrain maps help to isolate and zoom-in on priority places for optimal allocations of resources and effective crime prevention programming. Here's an award-winning example in Kansas City, Missouri. Paraphrased from "Risk-Based Policing" by Kennedy, Caplan & Piza (2018). See this book for complete references cited here.
|
RSS Feed
|
|
The official website of Risk Terrain Modeling (RTM) based out of Rutgers University and in partnership with Simsi
|